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Data Analytics based Deep Mayo Predictor for IPL-9

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
C. Deep Prakash, C. Patvardhan, C. Vasantha Lakshmi
10.5120/ijca2016911875

Deep C Prakash, C Patvardhan and Vasantha C Lakshmi. Data Analytics based Deep Mayo Predictor for IPL-9. International Journal of Computer Applications 152(6):6-11, October 2016. BibTeX

@article{10.5120/ijca2016911875,
	author = {C. Deep Prakash and C. Patvardhan and C. Vasantha Lakshmi},
	title = {Data Analytics based Deep Mayo Predictor for IPL-9},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {152},
	number = {6},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {6-11},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume152/number6/26321-2016911875},
	doi = {10.5120/ijca2016911875},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This paper presents a Deep Mayo Predictor model for predicting the outcomes of the matches in IPL 9 being played in April – May, 2016. The model has three components which are based on multifarious considerations emerging out of a deeper analysis of T20 cricket. The models are created using Data Analytics methods from machine learning domain. The prediction accuracy obtained is high as the Mayo Predictor Model is able to correctly predict the outcomes of 39 matches out of the 56 matches played in the league stage of the IPL IX tournament. Further improvement in the model can be attempted by using a larger training data set than the one that has been utilized in this work. No such effort at creating predictor models for cricket matches has been reported in the literature.

References

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Keywords

Mayo Predictor, Deep Analytics, IPL 9, Random Forest